September JAMIA Journal Club Webinar

September 14, 2017
3:00PM
4:00PM
EST
Fee: 
Free for AMIA members and students of Academic Forum member institutions; Others: $50
Presenters: 
John D'Amore, MS

Implementation of a scalable, web-based, automated clinical decision support risk-prediction tool for chronic kidney disease using C-CDA and application programming interfaces

Author John D'Amore will discuss this month's JAMIA Journal Club selection:

Samal L, D’Damore JD, Bates DW, Wright A. Implementation of a scalable, web-based, automated clinical decision support risk-prediction tool for chronic kidney disease using C-CDA and application programming interfaces. J Am Med Inform Assoc. 2017 July 20. https://doi.org/10.1093/jamia/ocx065 

https://academic.oup.com/jamia/article-lookup/doi/10.1093/jamia/ocx065

Presenter

John D'Amore, MS
President
Diameter Health
Newton, MA

John D'Amore is the President and Chief Strategy Officer of Diameter Health. Diameter Health enables clinical insights through the normalization, cleansing, de-duplication and enrichment of medical data from across the care continuum. This provides a single, unified source of longitudinal structured patient information which can be the basis for improved care and actionable analytics. John was formerly a VP at Allscripts, a leading electronic health record vendor. Previously he oversaw decision support, clinical informatics, cost accounting and customer experience analytics and reporting at Memorial Hermann Health System in Houston.

John serves as Technical Advisor to the National Committee for Quality Assurance (NCQA) and Editor on HL7 C-CDA Standard. He is a published researcher on quality measurement, predictive analytics and medical interoperability. He received his Masters in Clinical Informatics from the University of Texas School of Biomedical Informatics and his Bachelors in Biochemistry from Harvard College.

He also serves as adjunct faculty at Boston University in Health Informatics

Format

  • 40-minute discussion between the authors and the JAMIA Student Editorial Board moderators including salient features of the published study and its potential impact on practice.
  • 20-minute discussion of questions submitted by listeners via the webinar tools.

Interactive/Evaluations

  • Follow @AMIAinformatics and #JAMIAJC for Journal Club information.
  • Participants also receive short feedback surveys to evaluate the JAMIA JC webinar.

Managers

JAMIA Journal Club managers are JAMIA Student Editorial Board members:

Lucy Lu Wang, PhD Candidate, Department of Biomedical Informatics and Medical Education, University of Washington, Seattle, WA 


Tim Herr, PhD Candidate in Health and Biomedical Informatics, Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL


Citation

The PubMed citation for the paper under discussion is:

Samal L, D’Damore JD, Bates DW, Wright A. Implementation of a scalable, web-based, automated clinical decision support risk-prediction tool for chronic kidney disease using C-CDA and application programming interfaces. J Am Med Inform Assoc. 2017 July 20. https://doi.org/10.1093/jamia/ocx065

Students who are not AMIA members, but whose academic institutions are members of the Academic Forum, are eligible for a complimentary JAMIA Journal Club registration. Please contact Rob Rader at rob@amia.org for the discount code. In the email, please include: full name, Academic Department, and the primary Academic Forum representative of that Academic Department. Note that AMIA Student memberships are $50, which allow access to JAMIA, all JAMIA Journal Clubs, and other webinars of interest to the biomedical informatics community. 

Statement of Purpose

Patient-specific risk predictions are a form of clinical decision support that improve care by helping physicians to organize and synthesize various clinical data into a single metric. A number of popular risk-prediction models are the Framingham Cardiovascular Risk Score, the Atherosclerotic Cardiovascular Disease Risk Score, and the Gail Breast Cancer Risk Score. However, these methods require manual data entry and workflow interruptions, and many ambulatory practices face time and personnel challenges in incorporating them into practice to improve patient outcomes.

Given the widespread adoption of electronic health records, the authors hypothesized that CDS could leverage the EHR’s structured clinical data, such as laboratory results, to enable the automation of risk-prediction models in real time, per patient, for specific illnesses. Using kidney failure risk prediction, the authors developed a stand-alone CDS application that extracted data, performed calculations, and displayed recommendations in a manner that addressed the real-world constraints of ambulatory practices.

This research study is the first to establish the feasibility of low-cost stand-alone CDS using modern web technology and Consolidated Clinical Document Architecture (C-CDA) documents. Webinar attendees will consider applying this method to other disease states where using CDS to identify risk during the clinical encounter can inform the clinician-patient conversation, and, ultimately improve health outcomes. 

Target Audience

The target audience for this activity is professionals and students interested in biomedical and health informatics.

Learning Objective

After this live activity, the participant should be better able to:

  • Understand how Consolidated Clinical Document Architecture extracts can support analytics, along with downsides and pitfalls
  • Consider how standards based data extraction from EHRs can be used to create automated risk prediction CDS tools in the ambulatory care environment
  • Learn how low-cost, open-source tools can be bundled to create web-based applications, with a particular emphasis on non-relational (noSQL) data stores. 
     

Faculty

John D’Amore, MS
President
Diameter Health
Newton, MA

Accreditation Statement

The American Medical Informatics Association is accredited by the Accreditation Council for Continuing Medical Education to provide continuing medical education for physicians.

Credit Designation Statement

The American Medical Informatics Association designates this live activity for a maximum of 1 AMA PRA Category 1 Credit(s). Physicians should claim only the credit commensurate with the extent of their participation in the activity. 

Criteria for Successful Completion

Completion of this live activity is demonstrated by:

  • Viewing the live webinar
  • Optional submission of questions via webinar feature; option to follow @AMIAinformatics and tweet via #JAMIAJC
  • Completion of the evaluation survey emailed at the webinar's conclusion, and 
  • Verification of attendance through the participant's electronic report through the individual login to AMIA Central at www.amia.org. 

The physician participant will be able to generate a CME certificate through the AMIA automated system. 
For a certificate of completion, contact Pesha@amia.org.

Commercial Support

No commercial support was received for this activity.

Disclosure Policy

As a provider accredited by the ACCME, AMIA requires that everyone who is in a position to control the content of an educational activity disclose all relevant financial relationships with any commercial interest for 12 months prior to the educational activity.

The ACCME considers relationships of the person involved in the CME activity to include financial relationships of a spouse or partner.

Faculty and planners who refuse to disclose relevant financial relationships will be disqualified from participating in the CME activity. For an individual with no relevant financial relationship(s), the participants must be informed that no conflicts of interest or financial relationship(s) exist.

AMIA uses a number of methods to resolve potential conflicts of interest, including: limiting content of the presentation to that which has been reviewed by one or more peer reviewers; ensuring that all scientific research referred to conforms to generally accepted standards of experimental design, data collection, and analysis; undertaking review of the educational activity by a content reviewer to evaluate for potential bias, balance in presentation, evidence-based content or other indicators of integrity, and absence of bias; monitoring the educational activity to evaluate for commercial bias in the presentation; and/or reviewing participant feedback to evaluate for commercial bias in the activity.

Disclosures for this Activity

These faculty, planners, and staff who are in a position to control the content of this activity disclose that they and their life partners have no relevant financial relationships with commercial interests: 

JAMIA Journal Club planners: Tim Herr, Lucy Lu Wang
AMIA staff: Susanne Arnold, Pesha Rubinstein, Rob Rader

The following provide their disclosures of relevant financial relationships with commercial interests that have occurred within the previous 12 months:

Faculty: John D'Amore: Salary, Grant/Research Support, and Stockholder: Diameter Health

JAMIA Student Editorial Board Advisor Michael Chiang:
 
Grants/Research Support: NIH, NSF
Consultant: Novartis; Clarity Medical Systems (unpaid member of Scientific Advisory Board)

Instructions for Claiming CME/CE Credit

CME site (MyAMIA) works best with IE 8 or above version, Chrome, Safari, and Firefox.

  • Login to your account at amia.org; in upper right hand corner, click on AMIA Central
  • Go to “My Events" under Membership/Activities
  • Click “Apply for Credits" for this webinar
  • Follow the instructions on the Credit Registration page. Be sure both drop-down menus say “physician”
  • To print out your certificate, go to "My CME/CE Credits" under Membership/Activities.
  • Physicians will be able to print out or save their CME certificates.
  • Other attendees: if you require a certificate of participation, please contact pesha@amia.org

Contact Info

For questions about content or CE, email pesha@amia.org.